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Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile
Abstract
Non-informational cues, such as facial expressions, can significantly influence judgments and interpersonal impressions. While past research has explored how smiling affects business outcomes in offline or in-store contexts, relatively less is known about how smiling influences consumer choice in e-commerce settings when there is no face-to-face interaction. In this article, we use a longitudinal Airbnb dataset and a facial attribute classifier to quantify the effect of a smile in the host’s profile photo on property demand and identify factors that influence when a host’s smile is likely to have the biggest effect. A smile in the host’s profile photo increases property demand by 3.5% on average. This effect is moderated by a variety of host and property characteristics that provide evidence for the role of uncertainty underlying why smiling increases demand. Specifically, when there is greater uncertainty regarding either the quality of the accommodations or the interaction with the host, a host’s smile will have a greater effect on demand. Online experiments confirm this pattern, offering further support for uncertainty perceptions driving the effect of smiling on increased Airbnb demand, and show that the effect of smiling on demand generalizes beyond Airbnb.
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Past empirical evidence has indicated that employee affective delivery can influence customer reactions (e.g., customer satisfaction, service quality evaluation). This study extends previous research by empirically examining mediating processes underlying the relationship between employee affective delivery and customer behavioral intentions. Data were collected from 352 employee-customer pairs in 169 retail shoe stores in Taiwan. Results showed that the influence of employee affective delivery on customers' willingness to return to the store and pass positive comments to friends was indirect through the mediating processes of customer in-store positive moods and perceived friendliness. The study also indicated that employee affective delivery influences customers' time spent in store, which, in turn, influences customer behavioral intentions.
Recent reviewers have concluded that dispositions are not very reliably encoded in nonverbal behavior, although observers seem eager to use nonverbal information to decode the dispositions of others. A modified Brunswik lens model (E. Brunswik, 1956) and behavior mapping were used to examine the encoding and decoding of 8 interpersonal dispositions from nonverbal cues. First, 20 triads completed self-assessments and were videotaped during conversation. Next, 38 of their nonverbal behaviors were independently scored. Finally, 21 unacquainted peers rated all 60 conversers on the same dispositions. Across the 8 dispositions, encoding multiple correlations ranged from 0 to .62 and decoding ranged from .74 to .82. Achievement (self–other correlations) ranged from .18 to .45. Some implications of the results for interpersonal conflict and personality assessment are discussed.
Despite a multitude of studies on the motivators of sharing economy participation, we understand little about how cultural and social drivers affect an individual’s use of sharing services on an online platform. This paper examines the influence of cultural and social factors on a consumer’s participation in a sharing economy. We used Hofstede’s cultural dimensions theory and Ajzen’s theory of planned behavior to formulate the research model to predict the behavioral intention to book an accommodation using the Airbnb platform. To test the model, an empirical study was conducted by collecting survey data on Amazon Mturk from 401 participants. Findings provide evidence that all the cultural dimensions except for masculinity were found to have significant relationship with attitude toward booking on Airbnb. Moreover, social influence has no significant effect on booking intention on Airbnb. We offered academic and practical implications and suggested future research directions based on our findings.
The use of sellers' personal photographs online is ubiquitous in sharing economy platforms such as Airbnb. This paper addresses two questions. First, what type of personal photos do hosts choose to post on Airbnb? Second, which of the characteristics of their photos affects their perceived trustworthiness? We answer these questions by building a structural equation model of the relation between the characteristics of the photos and the perceived trustworthiness of the hosts. The antecedents of trust in this model were defined based on insights from psychology regarding first impressions. We found that the hosts' visual characteristics (e.g., gender) as revealed in their online photographs affect their perceived trustworthiness both directly and indirectly via attractiveness. We also found that image characteristics, which are not related directly to the traits of the host in the picture (e.g., photograph quality), play a significant role in trust inference. Interestingly, the hosts' choices of their personal photos suggest that they may not be aware of these effects.
Amazon’s Mechanical Turk (MTurk) is arguably one of the most important research tools of the past decade. The ability to rapidly collect large amounts of high-quality human subjects data has advanced multiple fields, including personality and social psychology. Beginning in summer 2018, concerns arose regarding MTurk data quality leading to questions about the utility of MTurk for psychological research. We present empirical evidence of a substantial decrease in data quality using a four-wave naturalistic experimental design: pre-, during, and post-summer 2018. During and to some extent post-summer 2018, we find significant increases in participants failing response validity indicators, decreases in reliability and validity of a widely used personality measure, and failures to replicate well-established findings. However, these detrimental effects can be mitigated by using response validity indicators and screening the data. We discuss implications and offer suggestions to ensure data quality.
One hypothesized reason for why a disproportionately low number of men enter caregiving fields is how such men are perceived. In two studies, drawing upon the Stereotype Content Model and the lack‐of‐fit model, we tested whether men would encounter more social (e.g., likeability bias) and economic (e.g., hiring or job opportunity bias) penalties than women in caregiving professions due to perceptions that men are less warm than women. In all three studies, we created job or employment materials in which the gender of the candidate or employee was manipulated. In Study 1, a female preschool teacher received higher warmth ratings than a male preschool teacher, which in turn predicted preference for the female teacher over the male teacher. In Study 2, a female social worker was rated more highly in warmth and job hireability than a male social worker; warmth also mediated the relationships between gender and both likeability and job hireability. In Study 3, a male preschool teacher was rated lower in warmth, likeability, job hireability, and job suitability than both a female preschool teacher and a preschool teacher with an unspecified gender. There were no differences between perceived competence of men and women in caregiving positions when competence was assessed. Implications for the factors that predict adverse reactions to and penalties against men in caregiving occupations, as well as interventions to combat the potential negative effects of such penalties on men's interest in caregiving careers, are discussed.
The nature of a person's motivation (whether it is intrinsic or extrinsic) is a key predictor of how committed they are to a task, and hence how well they are likely to perform at it. However, it is difficult to reliably communicate and make inferences about such fine nuances regarding another person's motivation. Building on the social functional view of emotion and the evolutionary and psychophysical characteristics of facial expression of emotions, this research suggests that displayed enjoyment, as evidenced by the size and type of someone's smile, can serve as a strong non-verbal signal of intrinsic motivation. Taking the perspective of both actors and observers, five studies show that people infer greater intrinsic motivation when they see others display large Duchenne (vs. small) smiles, and that actors intuit this relationship, strategically displaying larger and more Duchenne-like smiles if they have an accessible goal to signal intrinsic (vs. extrinsic or no specific) motivation.
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Past research indicates that patient perceptions of surgeon warmth and competence influence treatment expectancies and satisfaction with treatment outcomes. Stereotypes have a powerful impact on impression formation. The present research explores stereotypes about surgeon warmth and competence and investigates the extent to which surgeon gender influences perceptions of female and male surgeons. A between-subjects experiment was conducted online using crowdsourcing technology to derive a representative sample from the general population. Four hundred and fifteen participants were randomly assigned to evaluate the warmth and competence of males, females, surgeons, male surgeons, or female surgeons, using validated measures. Planned contrasts revealed that as a group, surgeons received higher warmth and competence ratings than non-surgeons (p = .007). Consistent with gender stereotypes, female surgeons received higher warmth ratings (p < .001) and lower competence ratings (p = .001) than male surgeons. The stereotype of surgeons held by the general public is that they are high in warmth and competence relative to other occupational groups. Surgeon gender appears to influence general beliefs about the warmth and competence of female and male surgeons.
Purpose
The purpose of this study is to examine the psychological factors that motivate travelers to consider reusing Airbnb.
Design/methodology/approach
This study proposes and tests an integrative model that synthesizes the Theory of Planned Behavior (TPB), Prospect Theory (PT), and other Airbnb relevant constructs (unique experience expectation (UEE), familiarity, and electronic word-of-mouth (eWOM)) as the primary determinants of the Airbnb repurchase intention using an SEM approach.
Findings
Both attitude and subject norms are significant determinants of repurchase intention whereas perceived behavioral control is not. In addition, perceived value and risk have only direct significant impacts on attitude and in turn, indirectly affect repurchase intention. UEE, familiarity and eWOM exert direct and indirect influences on repurchase intention.
Research limitations/implications
This study extends the body of knowledge by integrating TPB and PT to investigate consumer repurchase intention in Airbnb, which provides a theoretical baseline and serves as a starting point for exploring the structural relationships of Airbnb and the sharing economy.
Practical implications
Airbnb should place more emphasis on value packages and authentic/unique travel experience to retain and attract more travelers. More safety/security programs should be put in place and clearly communicated to reduce the perceived risks. In addition, Airbnb may publicize positive WOM and introduce and expand familiarity programs to incentivize Airbnb travelers.
Originality/value
This study explores the psychological reasons why travelers will re-patronize Airbnb, providing insights into the motives of Airbnb travelers. A clear understanding of Airbnb travelers’ repurchase intention will facilitate to develop effective strategies for Airbnb to induce positive repurchase behaviors.
Airbnb has grown very rapidly over the past several years, with millions of tourists having used the service. The purpose of this study was to investigate tourists’ motivations for using Airbnb and to segment them accordingly. The study involved an online survey completed in 2015 by more than 800 tourists who had stayed in Airbnb accommodation during the previous 12 months. Aggregate results indicated that respondents were most strongly attracted to Airbnb by its practical attributes, and somewhat less so by its experiential attributes. An exploratory factor analysis identified five motivating factors—Interaction, Home Benefits, Novelty, Sharing Economy Ethos, and Local Authenticity. A subsequent cluster analysis divided the respondents into five segments—Money Savers, Home Seekers, Collaborative Consumers, Pragmatic Novelty Seekers, and Interactive Novelty Seekers. Profiling of the segments revealed numerous distinctive characteristics. Various practical and conceptual implications of the findings are discussed.
Airbnb is an online marketplace for peer-to-peer accommodation rental services. In contrast to traditional rental services, personal profile images, i.e. the sellers’ facial images, are present along with the housing on offer. This study aims to investigate the impact of a seller’s facial image and their expression upon buyers’ behavior in this context. The impact of facial expressions was investigated together with other relevant variables (price and customer ratings). Findings from a conjoint study (n=139) show that the impact of a seller’s facial expression on buying behavior in an online peer-to-peer context is significant. A negative facial expression and absence of facial image (head silhouette) abates approach and evokes avoidance tendencies to explore a specific web page on Airbnb, and, simultaneously decrease the likelihood to rent. The reverse effect was true for neutral and positive facial expressions. We found that a negative and positive facial expression had more impact on likelihood to rent, for women than for men. Further analysis shows that the absence of facial image and an angry facial expression cannot be compensated for by a low price and top customer ratings related to likelihood to rent. Practitioners should keep in mind that the presence/absence of facial images and their inherent expressions have a significant impact in the peer-to-peer accommodation rental services.
Predicting face attributes from web images is challenging due to background
clutters and face variations. A novel deep learning framework is proposed for
face attribute prediction in the wild. It cascades two CNNs (LNet and ANet) for
face localization and attribute prediction respectively. These nets are trained
in a cascade manner with attribute labels, but pre-trained differently. LNet is
pre-trained with massive general object categories, while ANet is pre-trained
with massive face identities. This framework not only outperforms
state-of-the-art with large margin, but also reveals multiple valuable facts on
learning face representation as below.
(1) It shows how LNet and ANet can be improved by different pre-training
strategies.
(2) It reveals that although filters of LNet are fine-tuned by attribute
labels, their response maps over the entire image have strong indication of
face's location. This fact enables training LNet for face localization with
only attribute tags, but without face bounding boxes (which are required by all
detection works). With a novel fast feed-forward scheme, the cascade of LNet
and ANet can localize faces and recognize attributes in images with arbitrary
sizes in real time.
(3) It also demonstrates that the high-level hidden neurons of ANet
automatically discover semantic concepts after pre-training, and such concepts
are significantly enriched after fine-tuning. Each attribute can be well
explained by a sparse linear combination of these concepts. By analyzing such
combinations, attributes show clear grouping patterns, which could be well
interpreted semantically.
Purpose
– In this article, message appeals along with the moderating effect of gender are examined on frequently used measures of ad effectiveness (i.e. ad likability, attitude to the issue, and behavioral intention) in the emerging domain of pro-environmental social advertising. The paper aims to discuss these issues.
Design/methodology/approach
– This study employed a between-subjects 2 (gender)×3 (message appeal) factorial design, administered through a commercial online consumer panel firm based in the USA, which included 444 respondents across three markets: Australia, the UK and the USA.
Findings
– Results show that of three frequently used message appeals (rational, negative emotional, and positive emotional), rational ad appeals are not as effective as emotional appeals. The study also shows that females respond more strongly to negative emotional appeals than males, while there is no significant difference in how males and females responded to positive emotional or rational ad appeals. In addition, the study demonstrates that the measure of ad likability, which is frequently used as a reliable copy-test measure in commercial marketing situations, is not a valid measure of ad effectiveness in the context of social advertising.
Research limitations/implications
– While the study included participants from three countries, Australia, the UK and the USA, the obvious limitation of the experimental design lies in the limited sample size. Further, while the ads' cognitive processing load was kept consistent across the three conditions, it may be possible that linguistic nuances across these markets might affect the ads' processing demands from one market to another. The consistency of the study's manipulation checks, however, might serve to offer support for the copy approach taken here.
Originality/value
– This study reinforces previous studies in both the commercial and social marketing fields that suggest practitioners should be cautious of placing too much emphasis on this measure as an indicator of future ad performance.
Purpose
The purpose was to understand how service familiarity (i.e., the familiarity of the customer with the employee and service provided) operates as a boundary condition for the impact of employee positive emotional displays on service performance.
Design/Methodology/Approach
In Study 1, we assessed whether service familiarity (as rated by employees) moderated the relationship of employee-reported positive emotional displays and coworker ratings of service performance. In Study 2, through observed employee–customer exchanges, we tested whether customer-reported familiarity with the service context moderated the relationship between third-party-observed employee positive emotional displays and customer ratings of transaction satisfaction and employee friendliness.
Findings
Employee positive emotional displays had the strongest influence on evaluations of performance under low familiarity contexts. Thus, positive emotional displays served as a signal of good performance when there was limited preexisting information about the employee.
Implications
Service performance evaluations may be less influenced by employee positive emotional displays when the customer has a familiar relationship, suggesting that such displays from the employee are not always necessary. However, for encounters, employee positive emotional displays are more critical for signaling high quality service performance.
Originality/Value
This combination of studies is among the first to isolate the influence of service familiarity at two different levels of conceptualization and measurement using multi-source ratings of service performance.
This article examines the joint effect of issue capability and gender on risk taking. Across three studies, the authors show that the effect of issue capability is moderated by gender, depending on the compatibility between the goal orientation of the decision maker and the nature of the decision task. For decisions that are mainly driven by achievement of gains (e.g., investment decisions), men's risk-taking propensity is more influenced by their levels of issue capability than women's because the nature of the decision task is consistent with men's agentic orientation focused on the self. Conversely, for decisions that are mainly driven by avoidance of losses (e.g., insurance decisions), women's risk taking is more sensitive to issue capability than men's because the nature of such decisions is consistent with women's communion orientation. The authors analyze the betting data from the Daily Double in the Jeopardy! game show (Study 1).The results show that gender moderates the effect of issue capability on the actual betting behavior in Jeopardy! In Study 2, the authors test the underlying mechanism through mediation analyses of the focus of attention. In Study 3, the authors manipulate the task nature and demonstrate that men's risk taking is more sensitive to issue capability in investment decisions, whereas women's risk taking is more sensitive to issue capability in insurance decisions.
This study examined whether the psychological climate for service friendliness correlated positively with employee displayed positive emotions, and whether such positive emotional displays influenced customer purchase decision and customer reactions concerning an organization. Data were collected from 290 sales clerks in 156 retail shoe stores in Taiwan, and from 284 customers who were served by one of the sales clerks. Results indicated a positive relationship between psychological climate for service friendliness and employees’ displayed positive emotions. The study also indicated that employees’ positive emotional displays would increase customer willingness to return to the store and pass positive comments to friends.
In this research, we extend emotional labor theories to the customer domain by developing and testing a theoretical model of the effects of employee emotional labor on customer outcomes. Dyadic survey data from 285 service interactions between employees and customers show that employees' emotional labor strategies of deep and surface acting differentially influence customers' service evaluations and that customers' accuracy in detecting employees' strategies can intensify this impact. We also investigate the potential moderating effects of service type on the relationship between emotional labor and customer outcomes but find no support for such an effect.
The smile is perhaps the most widely studied facial expression of emotion, and in this article we examine its status as a sign of physical dominance. We reason, on the basis of prior research, that prior to a physical confrontation, smiles are a nonverbal sign of reduced hostility and aggression, and thereby unintentionally communicate reduced physical dominance. Two studies provide evidence in support of this prediction: Study 1 found that professional fighters who smiled more in a prefight photograph taken facing their opponent performed more poorly during the fight in relation to their less intensely smiling counterparts. In Study 2, untrained observers judged a fighter as less hostile and aggressive, and thereby less physically dominant when the fighters' facial expression was manipulated to show a smiling expression in relation to the same fighter displaying a neutral expression. Discussion focused on the reasons why smiles are associated with decreased physical dominance. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
Tested the view that the number of arguments in a message could affect agreement with a communication by serving as a simple acceptance cue when personal involvement was low but could affect agreement by enhancing issue-relevant thinking when personal involvement was high. In addition to manipulating the personal relevance of the communication topic, both the number and the quality of the arguments in the message were varied. In a pilot study with 46 undergraduates, when the issue was of low relevance, Ss showed more agreement in response to a message containing 6 arguments (3 strong and 3 weak) than to messages containing either 3 strong or 3 weak arguments. Under high involvement, however, the 6-argument message did not increase agreement over the message containing only 3 strong arguments. In the full experiment, 168 undergraduates received either 3 or 9 arguments that were either all cogent or all specious under conditions of either high or low involvement. The manipulation of argument number had a greater impact under low than under high involvement, but the manipulation of argument quality had a greater impact under high than low involvement. Results indicate that increasing the number of arguments in a message could affect persuasion whether or not the actual content of the arguments was scrutinized. (53 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
In Exp I, photos of 15 female target persons posing happy, neutral, and sad facial expressions were rated by 257 undergraduates for facial attractiveness using paired comparisons and Likert scales. Half of the raters were instructed to compensate for the effects of facial expression. Paired comparisons and Likert ratings were highly correlated. Target persons were less attractive when posing sad expressions than when posing neutral or happy expressions, which did not differ. In addition, independent ratings of 4 dimensions of the target persons' facial expression were obtained: pleasantness, surprise, intensity, and naturalness. Changes in these dimensions from the neutral to the happy and sad expressions and the corresponding changes in attractiveness were consistently related only to pleasantness, supporting the reinforcement-affect theory of attraction. Exp II, with 21 male undergraduates, related overall attractiveness to facial and bodily attractiveness. Both facial and bodily attractiveness were predictive of overall attractiveness, but the face was a slightly more powerful predictor. Results are discussed with respect to the stability of physical attractiveness, and alternative explanations of the mental-illness/physical-unattractiveness relation are proposed. (54 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The accuracy of strangers' consensual judgments of personality based on "thin slices" of targets' nonverbal behavior were examined in relation to an ecologically valid criterion variable. In the 1st study, consensual judgments of college teachers' molar nonverbal behavior based on very brief (under 30 sec) silent video clips significantly predicted global end-of-semester student evaluations of teachers. In the 2nd study, similar judgments predicted a principal's ratings of high school teachers. In the 3rd study, ratings of even thinner slices (6 and 15 sec clips) were strongly related to the criterion variables. Ratings of specific micrononverbal behaviors and ratings of teachers' physical attractiveness were not as strongly related to the criterion variable. These findings have important implications for the areas of personality judgment, impression formation, and nonverbal behavior. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Naturalistic observation at a bowling alley (
N = 1,793 balls) shows that bowlers often smiled when socially engaged, looking at and talking to others, but not necessarily after scoring a spare or a strike. In a 2nd study, bowlers (
N = 166 balls) rarely smiled while facing the pins but often smiled when facing their friends. At a hockey game, fans (
N = 3,726 faces) smiled both when they were socially involved and after events favorable to their team. Pedestrians (
N = 663) were much more likely to smile when talking but only slightly more likely to smile in response to nice weather than to unpleasant weather. These 4 studies suggest a strong and robust association of smiling with a social motivation and an erratic association with emotional experience. (29 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
This study focuses on the antecedents and consequences of displayed emotion in organizations. I propose that customers "catch" the affect of employees through emotional contagion processes. Results indicate that the display of positive emotion by employees is positively related to customers' positive affect following service encounters and to their evaluations of service quality. In a replication and extension of prior research, transaction busyness and employee emotional expressiveness are shown to predict displays of emotion by employees.
Theorists have argued that facial expressions of emotion serve the interpersonal function of allowing one animal to predict another's behavior. Humans may extend these predictions into the indefinite future, as in the case of trait inference. The hypothesis that facial expressions of emotion (e.g., anger, disgust, fear, happiness, and sadness) affect subjects' interpersonal trait inferences (e.g., dominance and affiliation) was tested in two experiments. Subjects rated the dispositional affiliation and dominance of target faces with either static or apparently moving expressions. They inferred high dominance and affiliation from happy expressions, high dominance and low affiliation from angry and disgusted expressions, and low dominance from fearful and sad expressions. The findings suggest that facial expressions of emotion convey not only a target's internal state, but also differentially convey interpersonal information, which could potentially seed trait inference.
Machine learning approaches have produced some of the highest reported performances for facial expression recognition. However, to date, nearly all automatic facial expression recognition research has focused on optimizing performance on a few databases that were collected under controlled lighting conditions on a relatively small number of subjects. This paper explores whether current machine learning methods can be used to develop an expression recognition system that operates reliably in more realistic conditions. We explore the necessary characteristics of the training data set, image registration, feature representation, and machine learning algorithms. A new database, GENKI, is presented which contains pictures, photographed by the subjects themselves, from thousands of different people in many different real-world imaging conditions. Results suggest that human-level expression recognition accuracy in real-life illumination conditions is achievable with machine learning technology. However, the data sets currently used in the automatic expression recognition literature to evaluate progress may be overly constrained and could potentially lead research into locally optimal algorithmic solutions.
This article examines conditions that influence consumers' use of persuasion knowledge in evaluating an influence agent, such as a salesperson. We propose that persuasion knowledge is used when consumers draw an inference that a persuasion motive may underlie a salesperson's behavior. These motive inferences then affect perceptions of the salesperson. We propose that two factors, the accessibility of persuasion motives and the cognitive capacity of the consumer, affect whether consumers use persuasion knowledge. When an ulterior persuasion motive is highly accessible, both cognitively busy targets and unbusy observers use persuasion knowledge to evaluate the salesperson. When an ulterior motive is less accessible, cognitively busy targets are less likely to use persuasion knowledge, evaluating the salesperson as more sincere than are cognitively unbusy observers. Several experiments find support for the predictions. Copyright 2000 by the University of Chicago.
This article develops a model of how customers with prior experiences and expectations assess service performance levels, overall service quality, and service value. The model is applied to residential customers' assessments of local telephone service. The model is estimated with a two-stage least squares procedure through survey data. Results indicate that residential customers' assessments of quality and value are primarily a function of disconfirmation arising from discrepancies between anticipated and perceived performance levels. However, perceived performance levels also were found to have an important direct effect on quality and value assessments. Copyright 1991 by the University of Chicago.
We study how Airbnb property demand changed after the acquisition of verified images (taken by Airbnb’s photographers) and explore what makes a good image for an Airbnb property. Using deep learning and difference-in-difference analyses on an Airbnb panel data set spanning 7,423 properties over 16 months, we find that properties with verified images had 8.98% higher occupancy than properties without verified images (images taken by the host). To explore what constitutes a good image for an Airbnb property, we quantify 12 human-interpretable image attributes that pertain to three artistic aspects—composition, color, and the figure-ground relationship—and we find systematic differences between the verified and unverified images. We also predict the relationship between each of the 12 attributes and property demand, and we find that most of the correlations are significant and in the theorized direction. Our results provide actionable insights for both Airbnb photographers and amateur host photographers who wish to optimize their images. Our findings contribute to and bridge the literature on photography and marketing (e.g., staging), which often either ignores the demand side (photography) or does not systematically characterize the images (marketing).
This paper was accepted by Juanjuan Zhang, marketing.
When do people call someone emotional? Why is it generally accepted that women are emotional and men are not? What are the actual differences between men and women with regard to specific emotions? Under what circumstances are these differences most pronounced? How can we explain these alleged differences? In this book a distinguished international group of scholars seek to address these and other questions in an attempt to disentangle the complex and fascinating relationship between gender and emotion. Presenting a systematic overview of the most recent social psychological research in this field, the contributors combine empirical evidence and theoretical explanations to examine a wide range of emotions and emotional expressions and how they vary according to gender and context.
This paper examines the long-run causal effects of management on firm performance. Under the United States Technical Assistance and Productivity Program (1952–1958), the United States organized management training trips for Italian managers to US firms and granted technologically advanced machines to Italian companies. I exploit an unexpected budget cut that reduced the number of participating firms and find that, compared to businesses excluded by the budget cut: performance of Italian firms that sent their managers to the United States increased for at least fifteen years after the program; performance of companies that received new machines increased, but flattened out over time; management and new machines were complementary.
This study investigates the attributes that influence Airbnb users’ experiences by analysing a “big data” set of online review comments through the process of text mining and sentiment analysis. Findings reveal that Airbnb users tend to evaluate their experience based on a frame of reference derived from past hotel stays. Three key attributes identified in the data include ‘location’, ‘amenities’ and ‘host’. Surprisingly, ‘price’ is not identified as
a key influencer. The analysis suggests a positivity bias in Airbnb users’ comments while negative sentiments are mostly caused by ‘noise’. This research offers an alternative approach and more coherent understanding of the Airbnb experience. Methodologically, it contributes by illustrating how big data can be used and visually interpreted
in tourism and hospitality studies.
We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 dif- ferent classes. On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0% which is considerably better than the previous state-of-the-art. The neural network, which has 60 million parameters and 650,000 neurons, consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully-connected layers with a final 1000-way softmax. To make training faster, we used non-saturating neurons and a very efficient GPU implemen- tation of the convolution operation. To reduce overfitting in the fully-connected layers we employed a recently-developed regularization method called dropout that proved to be very effective. We also entered a variant of this model in the ILSVRC-2012 competition and achieved a winning top-5 test error rate of 15.3%, compared to 26.2% achieved by the second-best entry
While previous work has focused on the positive impact of smiles on interpersonal perceptions, this research proposes and finds that smile intensity differentially affects two fundamental dimensions of social judgments-warmth and competence. A marketer displaying a broad smile, compared to a slight smile, is more likely to be perceived by consumers as warmer but less competent. Furthermore, the facilitative effect of smile intensity on warmth perceptions is more prominent among promotion-focused consumers and in low-risk consumption contexts, while the detrimental effect of smile intensity on competence perceptions is more likely to occur among prevention-focused consumers and in high-risk consumption situations. Field observations in a crowdfunding context further indicate that the effects of smile intensity on warmth and competence perceptions have downstream consequences on actual consumer behaviors. © The Author 2016. Published by Oxford University Press on behalf of Journal of Consumer Research, Inc. All rights reserved.
The appearance and expansion of Airbnb as part of the sharing economy have generated a growing debate in tourism scholarship. Within sub-Saharan Africa, South Africa is currently the major focus of Airbnb operations. This article investigates the recent proliferation of Airbnb's accommodation in Cape Town, South Africa's premier international tourist destination. Responding to changing tourist preferences and dynamic change in readily accessible technologies, Airbnb has found a niche in the tourist accommodation market left vacant by more traditional and formal tourist accommodation types. Despite its explosive expansion, little is known about this phenomenon in South Africa. This investigation seeks to address the limited scholarship on this tourist accommodation segment in South Africa in the empirical setting of Cape Town. Issues under scrutiny are the spatial and temporal development of Airbnb in Cape Town and the characteristics of Airbnb providers and guests.
Peer-to-peer business models rely on interpersonal communication for their success. In this article, we focus on Airbnb – an exemplar of the so-called ‘sharing economy’ – and more specifically, on Airbnb’s reciprocal reviewing system, which enables both hosts and guests to review one another. Our study takes a computer-assisted, qualitative approach to explore linguistic patterns of evaluation in Airbnb reviews. Our findings indicate that Airbnb reviews tend to comprise a very restricted set of linguistic resources, establishing the site’s norm of highly positive commentary, which in turn makes Airbnb reviews, on the surface, appear to be quite similar to one another. However, a micro-analytic comparison of positive reviews reveals that less-than-positive experiences are sometimes communicated using more nuanced, subtle cues. This study contributes to existing literature on electronic word of mouth in the tourism industry by highlighting how evaluation is communicated, while simultaneously responding to hospitality scholars’ calls for analyses which extend beyond the star ratings and also take into account consumers’ constructions of experience in the review texts themselves.
Communication scientists routinely ask questions about causal relationships. Whether it is examining the persuasive impact of public service announcements on attitudes and behavior, determining the impact of viewing political debates on political knowledge or voter turnout, or assessing whether success in achieving one's Internet browsing goals prompts greater interest in e-commerce, communication scholars frequently conduct research to answer questions about cause. Data analysis usually focuses on examining if the putative causal variable, whether manipulated or measured, is related to the outcome using a linear model such as analysis of variance or linear regression. In many arenas of research, such analyses, when accompanied by good research design, are sufficient to answer the question as to whether variation in X causes variation in Y. But deeper understanding accrues when researchers investigate the process by which a given effect is produced. Although it might be interesting and even important to discover, for mechanisms ...
‘Sharing economy’ platforms such as Airbnb have recently flourished in the tourism industry. The prominent appearance of sellers' photos on these platforms motivated our study. We suggest that the presence of these photos can have a significant impact on guests' decision making. Specifically, we contend that guests infer the host's trustworthiness from these photos, and that their choice is affected by this inference. In an empirical analysis of Airbnb's data and a controlled experiment, we found that the more trustworthy the host is perceived to be from her photo, the higher the price of the listing and the probability of its being chosen. We also find that a host's reputation, communicated by her online review scores, has no effect on listing price or likelihood of consumer booking. We further demonstrate that if review scores are varied experimentally, they affect guests' decisions, but the role of the host's photo remains significant.
Agency and communion are the core dimensions of social judgment as they indicate whether someone's intentions toward us are beneficial or harmful (i.e., communion), and whether they have the ability to fulfil their intentions (i.e., agency). Recent advances have demonstrated that communion encompasses both sociability (e.g., friendliness, likeability) and morality (e.g., honesty, trustworthiness) characteristics. In this article, we review the emerging literature highlighting that morality and sociability make unique contribution to social judgment and that morality has a primary role in the evaluations we make of individuals and groups. We also consider the evidence showing that morality and sociability play distinct roles in the positive evaluation of the individual and group self-concept. We conclude that future research on social judgment should expand the two-dimensional model to the more specific aspects of communion captured in information about morality and sociability.
Understanding how people form impressions of others is a key goal of social cognition research. Past theories have posited that two fundamental dimensions—warmth and competence—underlie impression formation. However, these models conflate morality with warmth and fail to capture the full role that moral character plays in impression formation. An emerging perspective separates moral character (or morality) from warmth on both theoretical and empirical grounds. When morality is pitted against warmth, morality is clearly a more important driver of impression formation, as revealed by correlational, experimental, and archival studies. Yet social warmth remains important and conveys distinct information that morality does not. Alongside competence, both factors matter not only for person perception but also for other aspects of social cognition, including group perception. Important unanswered questions remain regarding the perceived structure of moral character and the way it is appraised in everyday life.
The present study of 138 participants explored how facial expressions and gender stereotypes influence impressions. It was predicted that images of smiling women would be evaluated more favorably on traits reflecting warmth, and that images of non-smiling men would be evaluated more favorably on traits reflecting competence. As predicted, smiling female faces were rated as more warm; however, contrary to prediction, perceived competence of male faces was not affected by facial expression. Participants' female stereotype endorsement was a significant predictor for evaluations of female faces; those who ascribed more strongly to traditional female stereotypes reported the most positive impressions of female faces displaying a smiling expression. However, a similar effect was not found for images of men; endorsement of traditional male stereotypes did not predict participants' impressions of male faces.
Attitude theory is used to provide a conceptual analysis of how attitudes toward men and women relate to gender stereotypes. Consistent with this analysis, attitudes toward the sexes related positively to the evaluative meaning of the corresponding gender stereo-types. In addition, attitudes and stereotypes about women were extremely favorable - in fact, more favorable than those about men. The findings also demonstrated that the Attitudes Toward Women Scale assesses attitudes toward equal rights for women not attitudes toward women, and therefore did not relate to the evaluative meaning of subjects' stereotypes about women.
It was predicted that rapid onset and offset times of smiles are indicators of strategic or managed positive affect. Women (N = 96) were videotaped interacting with elementary-aged boys whose behavior (responsive, cooperative versus unresponsive, resistant) was likely to elicit positive versus negative affect. Adult smiles were found to fade faster when directed to unresponsive than to responsive children. Onset time of adult smiles, on the other hand, were found to vary as a function of caregiver attributions, that is, faster onset times were shown by "luck" than "ability" attributors. Fast offset time was interpreted as an indicator of unreciprocated positive affect (situational influence on smiling). Fast onset time of smiles was interpreted as reflecting an ingratiating self-presentation strategy (personal influence on smiling). Trends were observed indicating that slow onset and offset times of smiles acted to increase child responsiveness.
Purpose
– The purpose of this paper is to examine if the service worker's display of smiles in the service encounter has an effect on customer satisfaction.
Design/methodology/approach
– An experimental design was used in which participants (N=220) were randomly allocated to one of four service encounters. Two variables were manipulated; the service worker with whom the participant interacted had either a neutral facial expression or a smiling facial expression, and the service worker was either male or female.
Findings
– The smiling service worker produced a higher level of customer satisfaction than the neutral service worker, regardless of the sex of the service worker (and the sex of the participant). In addition, the results indicate that this outcome involved both emotional contagion and affect infusion.
Originality/value
– This paper extends the service literature's discourse on the impact of the service worker's smile behavior on customer satisfaction by including intermediate variables such as appraisals, emotions, and the attitude toward the service worker.
This article reports the results of an experimental investigation of the influence of a communicator’s characteristics on
respondent’s evaluation of an advertisement when the communicator is in the role of a spokesperson. Specifically, the author
assesses the impact of the physical attractiveness, sex and race of a spokesperson, the sex of the respondent and product
advertised on respondent’s attitude toward the advertisement, and respondent’s perceptions of the advertised product.
The results presented indicate that the effectiveness of the factors mentioned are dependent on the specific objective of
the communication. A main effect of physical attractiveness was noted on a subject’s attitude toward the advertisement, on
perceptions of product quality and intent to purchase. The sex of the communicator impacted on a subject's perception of product
quality and interacted with the race of the communicator to effect the intent to purchase variable. Race was shown to effect
the subject’s perception of product quality. A main effect of the sex of the subject was noted for the cognition variable.
Along with race and gender, people commonly use age to categorize—and form stereotypes about—others. Of the three categories, age is the only one in which the members of the in-group (the young) will eventually join the out-group (the old). Although ageism is found cross-culturally, it is especially prevalent in the United States, where most people regard growing older with depression, fear, and anxiety. Older people in the United States are stigmatized and marginalized, with often devastating consequences.
Although researchers have paid a great deal of attention to racism and sexism, there has been a dearth of research on ageism. A major reason for this neglect is that age prejudice is still considered socially acceptable. As baby boomers approach retirement age, however, there has been increased academic and popular interest in aging. This volume presents the current thinking on age stereotyping, prejudice, and discrimination by researchers in gerontology, psychology, sociology, and communication. The book presents theoretical and empirical findings on the origins and effects of ageism, as well as suggestions on how to reduce ageism for the approaching "graying of America."
Bradford Books imprint
Primitive emotional contagion has been proposed to explain why "service with a smile" predicts encounter satisfaction. We provide a comprehensive test of this mechanism by examining mimicry and mood as mediators in service encounters, contrasting such mediation with a direct path through perceived service quality. Independent coders recorded the strength of employees' and customers' smiles at three points in time during real service encounters, and 173 customers completed postencounter surveys. Mimicry effects were supported; however, only service quality appraisals, and not customers' affect, fully mediated the relationship of employee smiling and encounter satisfaction.
Americans stereotype elderly people as warm and incompetent, following from perceptions of them as noncompetitive and low status, respectively. This article extends existing research regarding stereotyping of older people in two ways. First, we discuss whether the mixed elderly stereotype is unique to American culture. Data from six non-U.S. countries, including three collectivist cultures, demonstrate elderly stereotypes are consistent across varied cultures. Second, we investigate the persistence of the evaluatively-mixed nature of the elderly stereotype. In an experiment, 55 college students rated less competent elderly targets (stereotype-consistent) as warmer than more competent (stereotype-inconsistent) and control elderly targets. We also discuss the type of discrimination—social exclusion—that elderly people often endure.
We construct two models of the behavior of consumers in an environment where there is uncertainty about brand attributes. In our models, both usage experience and advertising exposure give consumers noisy signals about brand attributes. Consumers use these signals to update their expectations of brand attributes in a Bayesian manner. The two models are (1) a dynamic model with immediate utility maximization, and (2) a dynamic “forward-looking” model in which consumers maximize the expected present value of utility over a planning horizon. Given this theoretical framework, we derive from the Bayesian learning framework how brand choice probabilities depend on past usage experience and advertising exposures. We then form likelihood functions for the models and estimate them on Nielsen scanner data for detergent.
We find that the functional forms for experience and advertising effects that we derive from the Bayesian learning framework fit the data very well relative to flexible ad hoc functional forms such as exponential smoothing, and also perform better at out-of-sample prediction. Another finding is that in the context of consumer learning of product attributes, although the forward-looking model fits the data statistically better at conventional significance levels, both models produce similar parameter estimates and policy implications. Our estimates indicate that consumers are risk-averse with respect to variation in brand attributes, which discourages them from buying unfamiliar brands.
Using the estimated behavioral models, we perform various scenario evaluations to find how changes in marketing strategy affect brand choice both in the short and long run. A key finding obtained from the policy experiments is that advertising intensity has only weak short run effects, but a strong cumulative effect in the long run.
The substantive content of the paper is potentially of interest to academics in marketing, economics and decision sciences, as well as product managers, marketing research managers and analysts interested in studying the effectiveness of marketing mix strategies. Our paper will be of particular interest to those interested in the long run effects of advertising.
Note that our estimation strategy requires us to specify explicit behavioral models of consumer choice behavior, derive the implied relationships among choice probabilities, past purchases and marketing mix variables, and then estimate the behavioral parameters of each model. Such an estimation strategy is referred to as “structural” estimation, and econometric models that are based explicitly on the consumer's maximization problem and whose parameters are parameters of the consumers' utility functions or of their constraints are referred to as “structural” models.
A key benefit of the structural approach is its potential usefulness for policy evaluation. The parameters of structural models are invariant to policy, that is, they do not change due to a change in the policy. In contrast, the parameters of reduced form brand choice models are, in general, functions of marketing strategy variables (e.g., consumer response to price may depend on pricing policy). As a result, the predictions of reduced form models for the outcomes of policy experiments may be unreliable, because in making the prediction one must assume that the model parameters are unaffected by the policy change.
Since the agents in our models choose among many alternative brands, their choice probabilities take the form of higher-order integrals. We employ Monte-Carlo methods to approximate these integrals and estimate our models using simulated maximum likelihood. Estimation of the dynamic forward-looking model also requires that a dynamic programming problem be solved in order to form the likelihood function. For this we use a new approximation method based on simulation and interpolation techniques. These estimation techniques may be of interest to researchers and policy makers in many fields where dynamic choice among discrete alternatives is important, such as marketing, decision sciences, labor and health economics, and industrial organization.
Research indicates that rejected individuals are better than others at discriminating between genuine (Duchenne) and deceptive (non-Duchenne) smiles (i.e., true versus false signals of affiliative opportunity). We hypothesized that rejected individuals would show a greater preference to work with individuals displaying Duchenne versus non-Duchenne smiles. To test this, participants wrote essays about experiences of inclusion, exclusion, or mundane events. They then saw a series of 20 videos of smiling individuals (10 with Duchenne and 10 with non-Duchenne smiles). Participants then indicated how much they would like to work with each target. Analyses revealed that compared to included and control participants, excluded individuals showed a greater preference to work with individuals displaying “real” as opposed to “fake” smiles. This effect was partially mediated by threats to “relational needs” (Williams, 2007) and fully mediated by threats to self-esteem. These results suggest that exclusion yields adaptive responses that could facilitate reconnection with others.